Shiqing Yu,Mathias Drton,Ali Shojaie
Shiqing Yu
Estimation of density functions supported on general domains arises when the data are naturally restricted to a proper subset of the real space. This problem is complicated by typically intractable normalizing constants. Score matching prov...
Matthew Hirn,Anna Little
Matthew Hirn
We propose a nonlinear, wavelet-based signal representation that is translation invariant and robust to both additive noise and random dilations. Motivated by the multi-reference alignment problem and generalizations thereof, we analyze the...
Saiprasad Ravishankar,Anna Ma,Deanna Needell
Saiprasad Ravishankar
Sparsity-based models and techniques have been exploited in many signal processing and imaging applications. Data-driven methods based on dictionary and sparsifying transform learning enable learning rich image features from data and can ou...
Vince Lyzinski,Daniel L Sussman
Vince Lyzinski
We consider the problem of graph matchability in non-identically distributed networks. In a general class of edge-independent networks, we demonstrate that graph matchability can be lost with high probability when matching the networks dire...
Xiuyuan Cheng,Alexander Cloninger,Ronald R Coifman
Xiuyuan Cheng
The paper introduces a new kernel-based Maximum Mean Discrepancy (MMD) statistic for measuring the distance between two distributions given finitely many multivariate samples. When the distributions are locally low-dimensional, the proposed...
Weighted mining of massive collections of [Formula: see text]-values by convex optimization [0.03%]
基于凸优化的大规模[Formula: see text]值集合的加权挖掘
Edgar Dobriban
Edgar Dobriban
Researchers in data-rich disciplines-think of computational genomics and observational cosmology-often wish to mine large bodies of [Formula: see text]-values looking for significant effects, while controlling the false discovery rate or fa...
Mihai Cucuringu,Amit Singer,David Cowburn
Mihai Cucuringu
The graph realization problem has received a great deal of attention in recent years, due to its importance in applications such as wireless sensor networks and structural biology. In this paper, we extend the previous work and propose the ...